Relationship between Particle and Plasma Properties and Coating Characteristics of Samaria-Doped Ceria Prepared by Atmospheric Plasma Spraying for Use in Solid Oxide Fuel Cells
Bibliographic record
Abstract
Abstract Samaria-doped ceria (SDC) has become a promising material for the fabrication of intermediate-temperature, metal-supported solid oxide fuel cells (SOFCs). While typical SOFC materials, such as yttria-stabilized zirconia (YSZ), require high temperatures (> 700°C) to exhibit suitable ionic conductivity for high cell performance, SDC displays similar ionic conductivities at lower temperatures (600°C – 650°C). The atmospheric plasma spray (APS) process is a promising technique for manufacturing metal-supported SOFCs. In this study, the in-flight characteristics, such as particle velocity and surface temperature, of spray-dried SDC agglomerates were analyzed at various plasma spray conditions using the DPV-2000 in-flight particle sensor manufactured by Tecnar Automation. Coatings of SDC were applied on stainless steel substrates using a range of spray conditions, and their resulting microstructures and deposition efficiencies were analyzed. It was found that particle temperature could be related to the specific plasma energy, and that coating porosity was related closely to the measured average particle temperature.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".